Contextual awareness is rapidly becoming a mandatory feature of many devices such as smartphones, laptops, AR/VR headsets, robots, hearables and wearables, driven by OEMs and IT companies looking to add value and enhance the user experience. The SenslinQ platform streamlines the development of these devices by centralizing the workloads that require an intimate understanding of the physical behaviors and anomalies of sensors. It collects data from multiple sensors within a device, including microphones, radars, Inertial Measurement Units (IMUs), environmental sensors, and Time of Flight (ToF), and conducts front-end signal processing such as noise suppression and filtering on this data. Then, applying advanced algorithms, SenslinQ creates context enablers such as activity classification, voice and sound detection, and presence and proximity detection. These context enablers can then be fused on-device or otherwise sent wirelessly (Bluetooth, Wi-Fi, NB-IoT) to a local edge computer or the cloud for determining and adapting the device to the environment in which it operates. The customizable hardware reference design is composed of three pillars connected using standard system interfaces: Arm or RISC-V MCU, CEVA-BX DSPs and a wireless connectivity island, such as RivieraWaves Bluetooth, Wi-Fi or Dragonfly NB-IoT platforms, or other connectivity standards provided by the customer or 3rd parties. The SenslinQ software includes a large portfolio of ready-to-use software libraries from CEVA and its ecosystem partners.
Ceva DSP - www.ceva-dsp.com